Bingzhe Zhou

Simulate, Refine and Integrate: Strategy Synthesis for Efficient SMT Solving

Satisfiability Modulo Theories (SMT) solvers are crucial in many applications, yet their performance is often a bottleneck. This paper introduces SIRISMT, a novel framework that employs machine learning techniques for the automatic synthesis of efficient SMT-solving strategies. Specifically, SIRISMT